Hi Peter,
ProteinProphet uses the PeptideProphet results, so if many peptides in
ProteinProphet show no phosphorylation, these peptides were identified
this way in PeptideProphet. I am not sure how to answer your first
question, as I know nothing about your actual data, and it is unlikely
to be a matter of fit for ProteinProphet anyway. For your benefit,
however, PeptideProphet and ProteinProphet do provide you with several
statistics and graphs that can indicate how well your data were modeled.
These can provide insight into adjusting your parameters for optimum
performance.
To answer your second question: I have seen many publications that do
this. I generally do not have a problem with it as long as peptide FDR
is defined and some sort of Occam's razor is applied to the protein
inference to name the minimum protein set. Personally, I apply a protein
FDR to my analyses, and you must also consider that this was a request
from a reviewer.
Cheers,
Mike
On 11/28/2013 8:14 PM, zion wrote:
Dear Brendan and Mike:
Thanks very much for your replies,
I have tried my dataset(phospho and membrane) by peptideprophet and
proteinprophet,
but after that, so few phophoproteins are shown to be confident at
protein FDR<=1% and strangely, most of the peptides in the
phophproteins have no phosphorylation.
So now i am wondering if my phospho- (or even membrane) protein
dataset is fit for proteinprophet?
Recently, i read one article from here:
http://www.matrixscience.com/blog/does-protein-fdr-have-any-meaning.html
Now my question is that, since some reviewers ask me to provide
peptide FDR and protein FDR ( i forgot to write both when submitting
my paper), if i just use peptide FDR (by percolator) and get the
protein by confident peptide ids and at least one unique peptide, is
it proper to describe the confident protein this way instead of
providing protein FDR?
Many thanks,
-Peter
On Thursday, November 28, 2013 1:28:51 AM UTC+8, Brendan MacLean wrote:
Hi Peter,
For more information on what Mike explains, I recommend this paper:
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2773710/
<http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2773710/>
Also, be careful about distinguishing whether your FDR<=1% is at
the unique peptide level or the peptide spectrum match (PSM)
level. The same phenomenon occurs between PSM FDR and unique
peptide FDR as between unique peptide FDR and protein FDR.
Namely, true discoveries are more likely to be repeated, and
therefore 1% FDR at the PSM level will grow above 1% for unique
peptides and again further for proteins, as Mike noted.
Your choice to include only proteins with >1 hit does improve this
growth in FDR, by applying a secondary filter, but it is by no
means foolproof with modern mass spectrometers and multi-run data
sets, depending on the number of spectra you collected versus the
number of proteins considered in your search. I have seen million
spectrum data sets where FDR was seriously underestimated against
a human FASTA with proteins for ~23,000 genes.
A good way to gain some insight on your true FDR is to have decoy
proteins in your FASTA that are never exposed to any of your
search criteria. This allows you to double-check FDR estimates
from the statistical tools you use. Once you gain familiarity
with your tools, this may be come less necessary, but I have seen
statistical tools get these numbers wrong, for exactly these reasons.
Good luck with your FDR statistics.
--Brendan
On Tuesday, November 26, 2013 8:52:25 PM UTC-8, zion wrote:
Dear All:
If there are some confident peptide ids at FDR<=1% at the
peptide level,
when inferring proteins by confident peptides and at least one
unique peptide, CAN i say that at the protein level, its FDR<=1%?
Many thanks,
-Peter
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